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Mathematical Problems in Engineering
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2015
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Article
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Tab 6
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Research Article
Sample-Based Extreme Learning Machine with Missing Data
Table 6
Performance comparisons with UCI benchmark data sets. The two rows of each cell represent mean RMSE ± standard deviation over different missing ratios and training time (in seconds).
S-ELM
ZF-ELM
MF-ELM
Body fat
0.1299 ± 0.0905
0.1781 ± 0.1007
0.1457 ± 0.1088
0.1560
0.1758
0.1872
Housing
0.2229 ± 0.1019
0.3234 ± 0.1697
0.2511 ± 0.1261
0.5628
0.3432
0.3869
Pyrim
0.3816 ± 0.0842
0.5603 ± 0.2253
0.4537 ± 0.1396
0.0624
0.1008
0.0926
Abalone
0.2336 ± 0.1083
0.3004 ± 0.1537
0.2643 ± 0.1193
213.5
177.6
182.4
Bike sharing
0.3886 ± 0.1020
0.4662 ± 0.1596
0.3977 ± 0.1218
7.263
7.109
6.993
Airfoil self-noise
0.3765 ± 0.1591
0.4563 ± 0.2470
0.3810 ± 0.1928
52.38
50.74
51.61